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The bat sarbecovirus RaTG13 is a close relative of SARS-CoV-2, the cause of the COVID-19 pandemic. However, this bat virus was most likely unable to directly infect humans since its Spike (S) protein does not interact efficiently with the human ACE2 receptor. Here, we show that a single T403R mutation increases binding of RaTG13 S to human ACE2 and allows VSV pseudoparticle infection of human lung cells and intestinal organoids. Conversely, mutation of R403T in the SARS-CoV-2 S reduces pseudoparticle infection and viral replication. The T403R RaTG13 S is neutralized by sera from individuals vaccinated against COVID-19 indicating that vaccination might protect against future zoonoses. Our data suggest that a positively charged amino acid at position 403 in the S protein is critical for efficient utilization of human ACE2 by S proteins of bat coronaviruses. This finding could help to better predict the zoonotic potential of animal coronaviruses. The bat sarbecovirus RaTG13 is a close relative of SARS-CoV-2, but its spike protein doesn’t efficiently bind human ACE2. Here, the authors show that exchange of spike residue 403 between RaTG13 and SARS-CoV-2 spike proteins affects binding to human ACE2 and entry of pseudotyped viruses.

Utilization of human ACE2 allowed several bat coronaviruses (CoVs), including the causative agent of COVID-19, to infect humans directly or via intermediate hosts. However, the determinants of species-specific differences in ACE2 usage and the frequency of the ability of animal CoVs to use human ACE2 are poorly understood. Here we applied VSV pseudoviruses to analyze the ability of Spike proteins from 26 human or animal CoVs to use ACE2 receptors across nine reservoir, potential intermediate and human hosts. We show that SARS-CoV-2 Omicron variants evolved towards more efficient ACE2 usage but mutation of R493Q in BA.4/5 and XBB Spike proteins disrupts utilization of ACE2 from Greater horseshoe bats. Variations in ACE2 residues 31, 41 and 354 govern species-specific differences in usage by coronaviral Spike proteins. Mutation of T403R allows the RaTG13 bat CoV Spike to efficiently use all ACE2 orthologs for viral entry. Sera from COVID-19 vaccinated individuals neutralize the Spike proteins of various bat Sarbecovirus es. Our results define determinants of ACE2 receptor usage of diverse CoVs and suggest that COVID-19 vaccination may protect against future zoonoses of bat coronaviruses. Analysis of the ability of Spike proteins from 26 human or animal coronaviruses (CoVs) to use ACE2 receptors across nine reservoir, potential intermediate, and human hosts reveals determinants of ACE2 receptor usage for diverse CoVs.

Simian immunodeficiency viruses (SIVs) have crossed from apes to humans at least four times, but only one event gave rise to the AIDS pandemic. The host barriers that pandemic HIV-1 group M (major) strains overcame to spread efficiently in humans remain poorly understood. To identify such barriers, we performed CRISPR-Cas9 screens driven by the replication efficiency of SIVcpz, the chimpanzee precursor of HIV-1. Guide RNA libraries targeting more than 500 human genes encoding potential antiviral factors were inserted into the replication-competent SIVcpz MB897 molecular clone, which is phylogenetically closely related to HIV-1 group M strains. Propagation in Cas9-expressing human SupT1 T cells significantly enriched for sgRNAs targeting ADAR, AXIN1, CEACAM3, CD72, EHMT2, GRN, HMOX1, HMGA1, ICAM2, CD72, IFITM2, MEFV, PCED1B, SGOL2, SMARCA4, SUMO1 and TMEM173. These hits only partially overlapped with those identified in analogous HIV-1–based screens, indicating virus-specific restriction profiles. Functional analyses confirmed that IFITM2 (interferon-induced transmembrane protein 2), PCED1B (PC-esterase domain–containing protein 1B), MEFV (Mediterranean fever protein, pyrin/TRIM20), and AXIN1 (Axis inhibition protein 1), restrict replication of SIVcpz but not of HIV-1 group M strains in primary human CD4⁺ T cells. These findings reveal previously unrecognized host factors that limit SIVcpz replication in human cells and highlight barriers that HIV-1 likely overcame during its adaptation for pandemic spread. CRISPR screens with replication-competent SIVcpz identify human antiviral factors limiting efficient viral replication after zoonotic transmission.

Utilization of human ACE2 allowed several bat coronaviruses (CoVs), including the causative agent of COVID-19, to infect humans either directly or via intermediate hosts. Here, we analyzed the ability of Spike proteins from 24 human or animal CoVs to use ACE2 receptors across nine reservoir, potential intermediate and human hosts. We show that overall SARS-CoV-2 Omicron variants evolved more efficient ACE2 usage but mutation of R493Q in BA.5 Spike disrupts utilization of ACE2 from Greater horseshoe bats. Spikes from most CoVs showed species-specific differences in ACE2 usage, partly due to variations in ACE2 residues 31, 41 or 354. Mutation of T403R allowed the RaTG13 bat CoV Spike to use all ACE2 orthologs analysed for viral entry. Sera from COVID-19 vaccinated individuals neutralized the Spike proteins of a range of bat Sarbecoviruses. Our results define determinants of ACE2 receptor usage of diverse CoVs and suggest that COVID-19 vaccination may protect against future zoonoses of SARS-CoV-related bat viruses. Mutation of R493Q in BA.5 Spike disrupts utilization of ACE2 from Greater horseshoe bats Variations in ACE2 residues 31, 41 or 354 affect utilization by coronavirus Spike proteins Residue R403 in the Spike protein of bat coronavirus allow broad and effective ACE2 usage Sera from COVID-19 vaccinated individuals neutralize Spike proteins of bat Sarbecoviruses

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the COVID-19 pandemic, most likely emerged from bats1. A prerequisite for this devastating zoonosis was the ability of the SARS-CoV-2 Spike (S) glycoprotein to use human angiotensin-converting enzyme 2 (ACE2) for viral entry. Although the S protein of the closest related bat virus, RaTG13, shows high similarity to the SARS-CoV-2 S protein it does not efficiently interact with the human ACE2 receptor2. Here, we show that a single T403R mutation allows the RaTG13 S to utilize the human ACE2 receptor for infection of human cells and intestinal organoids. Conversely, mutation of R403T in the SARS-CoV-2 S significantly reduced ACE2-mediated virus infection. The S protein of SARS-CoV-1 that also uses human ACE2 also contains a positive residue (K) at this position, while the S proteins of CoVs utilizing other receptors vary at this location. Our results indicate that the presence of a positively charged amino acid at position 403 in the S protein is critical for efficient utilization of human ACE2. This finding could help to predict the zoonotic potential of animal coronaviruses.

Many studies have been conducted on the prediction of nitrous oxide (N2O) emissions from soils. Comparably, prediction of N2O water–air emissions is much more limited, especially at the national level. Here, we collected published N2O emission data across China's watersheds and analyzed spatiotemporal patterns during dry and wet seasons. We predicted N2O emission fluxes from these waterbodies for 2026–2028 using a traditional gray prediction model (GM) coupled with several deep learning models: Long Short‐Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional Long Short‐Term Memory (BiLSTM). The study showed large regional variation in emissions from subtropical to boreal watersheds. Average emission rates varied from 13.95 (±27.15) μg m−2 h−1 in the Yellow River Basin to 68.71 (±102.62) μg m−2 h−1 in Southwest China. N2O emissions were clearly higher in the dry season than the wet season in all regions except the Yellow River Basin, indicating strong influence from wetland vegetation. Regarding model performance, higher accuracy was achieved by GRU and BiLSTM, which successfully predicted fluctuating increases of N2O emission fluxes in most regions from 2026 to 2028, reflecting seasonal changes. While LSTM performed less accurately, GRU and BiLSTM, evolved from LSTM, may be more appropriate for complex situations. These findings provide insights into national spatiotemporal patterns of N2O emissions and can guide regional and national mitigation strategies as well as future research.

The spectral-element method (SEM) for simulating wave propagation is widely used with adjoint methods for full-waveform inversion. Typically, SEM is used to compute forward and adjoint wavefields, which is then applied to evaluate the Fréchet derivatives for updating the seismic structural model. The Hessian is rarely computed as the high computational and storage costs, although it can improve the accuracy of the model update and model convergence. Instead the approximate Hessian is determined, which is obtained with less computational effort. We present a method for simultaneously constructing Fréchet and Hessian kernels on the fly, which we call Multi-solver spectral-element and adjoint methods (Multi-SEM). Rather than storing all the wavefields, Multi-SEM is computed on the fly and requires only about a 2-fold computational cost when compared to the computation of Fréchet kernels. Numerical examples demonstrate the functionality of the method and the computer codes are provided with this contribution.

We introduce a technique to compute exact anelastic sensitivity kernels in the time domain using parsimonious disk storage. The method is based on a reordering of the time loop of time-domain forward/adjoint wave propagation solvers combined with the use of a memory buffer. It avoids instabilities that occur when time-reversing dissipative wave propagation simulations. The total number of required time steps is unchanged compared to usual acoustic or elastic approaches. The cost is reduced by a factor of 4/3 compared to the case in which anelasticity is partially accounted for by accommodating the effects of physical dispersion. We validate our technique by performing a test in which we compare the \\(K_\\alpha\\) sensitivity kernel to the exact kernel obtained by saving the entire forward calculation. This benchmark confirms that our approach is also exact. We illustrate the importance of including full attenuation in the calculation of sensitivity kernels by showing significant differences with physical-dispersion-only kernels.